Traditionally, at the edge of a mobile network only specialist processing was performed. The edge of a mobile network housed specialized computing devices that were designed from the ground up to perform a function in the overall architecture and were not able to be repurposed. Connectivity from the edge of the mobile network back to the core was also a specific configuration, running over specialized protocols. The complete configuration was optimized in the pre smartphone era, where voice quality was the key driver in network design and before the days where IP was the standard for network communications. Currently, IP has spread from the internet, to enterprise networks and with widespread adoption of LTE, through the edge of networks to the end devices. This has enabled new applications to emerge that have seen a transformation in telecommunication networks and their design.
Mobile edge computing (MEC) brings traditional Information Technology (IT) infrastructure deep into the mobile network to the radio access network (RAN). MEC separates functionality from the underlying hardware infrastructure to increase mobile network flexibility, economy and scale. MEC empowers computational power into the mobile RAN, and it promotes virtualized software based ecosystems at the radio edge. The MEC platforms enable virtualized applications to run much closer to mobile users to boost the user experience.
With advancement in technology, integration of Internet of things (IoT) devices in the MEC environment has been implemented. Currently, large numbers of IoT sensor nodes are interconnected and generate voluminous data based on the characteristics of the participants in IoT sensor nodes. IoT sensor nodes have limited capacity, usually operating in a constrained wireless network. In addition, the IoT sensor nodes may act as the server in an IoT environment. It is difficult for MEC server to retrieve the necessary contextual information from the IoT sensor nodes in an MEC environment. Further, MEC server has to request and collect the information related to the type of IoT sensor nodes, device specification, type of data, utilization information, and the like, for each of the IoT sensor nodes. This increases the processing time as well as load not only at the IoT sensor nodes but also at the MEC to contextualize the information for radio-network and users. Thus, there is a need of a communication technique for managing the IoT ecosystem into the existing MEC infrastructure such that communication among various participants of the MEC infrastructure and the one or more IoT sensor nodes may be streamlined.
Further limitations and disadvantages of conventional and traditional approaches will become apparent to one of skill in the art, through comparison of described systems with some aspects of the present disclosure, as set forth in the remainder of the present application and with reference to the drawings.